Koen

The Doctors Trio

We left behind quite an exciting couple weeks. PopEcol fledged its first cohort of PhDs. Tina, Sam and Koen successfully defended their four years of research and received their doctoral degrees.

They are not only our first PhD fledglings, but also among the founding members of PopEcol. It was difficult to say bye to the trio, who has been with us since the beginning of our group. We can only hope that this separation anxiety gets easier with future fledglings.

We wish them all the best for their future (and very much hope to be a part of that future)! 🙂

Here are the proud carriers of the amazing PhD hats:

Tina Cornioley

Thesis title: “Trait-mediated effects of climate on the population dynamics of the wandering albatross (Diomedea exulans)”

 

 

 

 

 

 

 

Sam Cruickshank

Thesis title: “Dealing with uncertainty in amphibian and reptile population monitoring for conservation”

 

 

 

 

 

 

 

Koen van Benthem

Thesis title: “Trait-based mechanistic and phenomenological approaches for predicting population dynamics”

 

Attendance ‘Bayesian population analyis using WinBUGS’-course

‘Don’t feign to be stupid.’ This well-chosen phrase of Marc Kéry introduced some of our group members to the world of Bayesian Statistics (where the use of your previous knowledge on the parameter you’re interested in, the prior distribution, plays a role). Together with Michael Schaub, Marc taught the inspiring course entitled ‘Bayesian population analysis using WinBUGS’ based on the book of the same name.

I was impressed by how they managed to cover almost the whole book within 5 days: starting with a gentle introduction to the analysis of distribution, abundance and population dynamics using a Bayesian framework, followed by an introduction to the software WinBUGS and implementation of mixed models in it, and finishing with some examples of the implementation of Integrated Population Models in WinBUGS. Lectures were alternated with useful exercises.

I think all the participants are after this course better trained in making a balanced decision whether they want to make use of the full knowledge they have, or use the veil of stupidity to make big discoveries (Schwartz, 2008).

BPA

Koen van Benthem | PhD Student

KoenMy research focuses on early warning signals: how can we predict critical transitions in populations. The aim is to base these predictions on a mechanistic understanding, rather than the predictions being purely phenomenological. To this end I will work with multiple long-term datasets. I will try to balance my work between more empirical and more theoretical approaches, such as the Price equations and its extensions. These two approaches will complement each other and create the desired more mechanistic understanding.

 

CV

  • 2013-present, PhD student, Institute of Evolutionary Biology and Environmental Studies,
    University of Zurich, Switzerland
  • 2011-2013, MSc in Natural Sciences, Radboud University Nijmegen, The Netherlands
  • 2008-2011, BSc in Natural Sciences, Radboud University Nijmegen, The Netherlands

Predicting population responses to environmental change

species2A major goal in biodiversity conservation is to predict responses of biological populations to environmental change. To achieve this goal, we must identify early warning signals of the demographic changes that underlie sudden population declines or explosions. Some studies have achieved phenomenological prediction of sudden changes, but recent advances that link trait-based information with demography hint that a mechanistic understanding is within reach. We are developing a predictive framework by investigating how wildlife populations respond demographically, ecologically and evolutionarily to environmental change, and identifying the demographic and phenotypic statistics that can be used as early warning signals of population change. This project will exploit nine unique mammalian systems to identify early warning signals of population change and test these signals on two experimental systems. The results will hopefully provide much-needed predictive insight into how wildlife populations respond to rapid environmental change.

species1


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